Exploring the outcomes of community based dental interventions delivered by dental students for people experiencing homelessness: A scoping review
Bibliographic record
Abstract
Background: People experiencing homelessness (PEH) have significantly poorer oral health compared to the general population, with barriers to dental care exacerbating health inequalities. Community-based dental interventions delivered by dental students offers a potential solution for improving oral health among PEH. Objectives: This scoping review aims to map existing literature on community-based dental interventions provided by dental students to PEH and to explore the reported outcomes of these from the perspectives of PEH. Methods: A scoping review was conducted using the PRISMA-ScR checklist. The comprehensive search was conducted across multiple databases and reference lists were hand searched. The Population, Concept, Context (PCC) framework using Joanna Briggs Institute (JBI) methodology was followed to guide the search strategy and eligibility criteria. Studies were screened against the eligibility criteria by two reviewers. Results: Six studies met the inclusion criteria, originating from the UK, Australia, the USA, and Canada. Interventions included oral health education and clinical treatments. Thematic analysis identified two overarching themes: ‘experience of the intervention’ and ‘impact of the intervention.’ High levels of satisfaction were reported, with participants noting improved oral health knowledge and intentions to improve oral health behaviours. Conclusions: Community-based dental interventions were well-received by PEH and led to improved oral health knowledge, oral health behaviour change and psychosocial wellbeing. The interventions fostered dignity and trust through respectful care, while also enriching dental education by promoting empathy and social accountability. Despite promising short-term outcomes, further inclusive and longitudinal research is needed to assess long-term impact and global relevance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".